• Journal of the Korea Society of Computer and Information
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• v.23 no.9
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• pp.27-34
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• 2018

Personal media centered on blogs, Twitter, and Facebook has opened up a personal broadcasting area while meeting platforms such as YouTube and Africa TV. Due to the many advantages and disadvantages of personal broadcasting, a study on it was necessary and statistical survey was conducted. The study conducted opinion survey of 118 university students on personal broadcasting. As a result, we are getting news using smartphones and mainly watching videos through YouTube, and watching videos type in the order of games, music videos and sports. Satisfaction rate of video was 72.4%, 80.2% of survey did not use paid services, experiences about personal broadcasting was 96.6% and 90.5% of survey the prospect of person broadcasting of the opinion that "it will be expanded". The first thing we want to be improved in personal broadcasting is the prevention of abusive language and hate speech. Second, we were reluctant to sensational content. Third, the survey results are the improvement of excessive advertising.

• Health Policy and Management
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• v.12 no.4
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• pp.56-67
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• 2002

The objectives of this study were to look into the present conditions and problems of smoking prevention programs for young people carried out by the Korean health insurance corporation(KHIC) and to provide the basic data for the governmental policy. In order to examine the actual achievements of existing smoking cessation programs, a survey was conducted over 235 KHIC branches. The person responsible for the cessation program from each branch responded to questionnaire sent by mail with regard to smoking cessation programs The survey shows the shortage of responsible persons. educational subjects were mainly elementary, middle school and high school students. The main educational method was to watch the video of which the content is the knowledge of smoking. but most of these videos were made for adults. Therefore, these videos are not appropriate for the children. 37% of these branches estimated the effectiveness of their program. On the basis of the survey data and analysis of current situations, the following actions are recommended in order to develop a more effective cessation program; first, the establishment of the effective administrative plan, second, the supplementation of the educator and the responsible person, third, the development of text books and videos which are appropriate for the children.

• Journal of Korea Game Society
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• v.17 no.6
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• pp.29-38
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• 2017

Predicting the user's reaction to the game at the stage of developing the game is important because it is related to the popularity of the game. In this paper, we propose a system that can collect and analyze game user's biometric information in a non-invasive way. To this end, we developed a mouse with skin conductance, pressure, gyroscope, and accelerometer sensor using Arduino. In order to verify the usefulness of this system, the subject was experimented with playing the first person shooter game with this mouse. We analyzed the gameplay videos recorded during Blizzard's 'OverWatch' and the bio-information collected from various sensors in the mouse.

• PNF and Movement
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• v.14 no.3
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• pp.209-217
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• 2016

Purpose: Treatments using a mirror neuron system, such as 3D virtual reality therapy, are used in stroke rehabilitation, but they need to be constructed according to a detailed procedure. The aims of this study were to analyze electroencephalograms (EEG) during relaxation and action while observing first person perspective (1AE) and third person perspective (3AE) videos of the right hand for 20's. Methods: Thirty participants (Male=4, Female=26) were recruited for this study. Participants were selected by a vividness of movement imagery questionnaire (VMIQ). EEG was measured during relaxxation and during action with 1AE and 3AE videos, focusing on the supination and pronation actions of participants' right hands. An absolute mu rhythm, a relatively high alpha power, and a relative beta power were identified. In each group, one-way repeated measures ANOVA was used for statistical analysis. Results: Measurement of absolute mu rhythms was significantly suppressed for both 1AE and 3AE compared with relaxation in C3 and C4 regions. High alpha wave measurements were significantly suppressed for both 1AE and 3AE in all regions, while beta wave measurements were significantly increased only for 3AE in F3 and F4 regions. Conclusion: Based on this study, we suggest that the mirror neuron system is activated during actions accompanied by action observation, especially actions with 3AE video observation, which can be a great therapeutic mathod in stroke rehabilitation.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.89-98
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• 2007

For browsing, searching, and manipulating video documents, an indexing technique to describe video contents is required. Until now, the indexing process is mostly carried out by specialists who manually assign a few keywords to the video contents and thereby this work becomes an expensive and time consuming task. Therefore, automatic classification of video content is necessary. We propose a fully automatic and computationally efficient method for analysis and summarization of spots news video for 5 spots news video such as soccer, golf, baseball, basketball and volleyball. First of all, spots news videos are classified as anchor-person Shots, and the other shots are classified as news reports shots. Shot classification is based on image preprocessing and color features of the anchor-person shots. We then use the dominant color of the field and motion features for analysis of sports shots, Finally, sports shots are classified into five genre type. We achieved an overall average classification accuracy of 75% on sports news videos with 241 scenes. Therefore, the proposed method can be further used to search news video for individual sports news and sports highlights.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.3
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• pp.1390-1403
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• 2016

Facial expression recognition (FER) plays a very significant role in computer vision, pattern recognition, and image processing applications such as human computer interaction as it provides sufficient information about emotions of people. For video-based facial expression recognition, depth cameras can be better candidates over RGB cameras as a person's face cannot be easily recognized from distance-based depth videos hence depth cameras also resolve some privacy issues that can arise using RGB faces. A good FER system is very much reliant on the extraction of robust features as well as recognition engine. In this work, an efficient novel approach is proposed to recognize some facial expressions from time-sequential depth videos. First of all, efficient Local Binary Pattern (LBP) features are obtained from the time-sequential depth faces that are further classified by Generalized Discriminant Analysis (GDA) to make the features more robust and finally, the LBP-GDA features are fed into Hidden Markov Models (HMMs) to train and recognize different facial expressions successfully. The depth information-based proposed facial expression recognition approach is compared to the conventional approaches such as Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Linear Discriminant Analysis (LDA) where the proposed one outperforms others by obtaining better recognition rates.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.10 no.6
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• pp.2767-2780
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• 2016

Video-based human-activity recognition has become increasingly popular due to the prominent corresponding applications in a variety of fields such as computer vision, image processing, smart-home healthcare, and human-computer interactions. The essential goals of a video-based activity-recognition system include the provision of behavior-based information to enable functionality that proactively assists a person with his/her tasks. The target of this work is the development of a novel approach for human-activity recognition, whereby human-body-joint features that are extracted from depth videos are used. From silhouette images taken at every depth, the direction and magnitude features are first obtained from each connected body-joint pair so that they can be augmented later with motion direction, as well as with the magnitude features of each joint in the next frame. A generalized discriminant analysis (GDA) is applied to make the spatiotemporal features more robust, followed by the feeding of the time-sequence features into a Hidden Markov Model (HMM) for the training of each activity. Lastly, all of the trained-activity HMMs are used for depth-video activity recognition.

• The Korean Journal of Emergency Medical Services
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• v.6 no.1
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• pp.65-75
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• 2002

This study was designed to develop e-Learning multimedia contents to provide the first aid rescuer with the basic resuscitation, members of the public, corporations and any other institutions who wish to learn this skills. It is carried out from October to December in 2001. This program was constructed on the basic of the network-instructional system Design model, this model has severalprogressive steps, which includes the planning, analysis of the contents, development of the contents, instructional design, development of web-based and multimedia, pilot test, implement, and evaluation. The URL of this site is http://www.cyber.hc.ac.kr named as the cyber education program for the basic resuscitatingskill. This contents consisted of 8 chapters providing as follows : Introduction, anatomy and physiology of heart-ling, Adult Cardio-Pulmonary Resuscitation, Adult Foregin-body Air-Obstruction, Child Cardio-Pulmonary Resuscitation, Child Foregin-body Air-Obstruction, Infant Cardio-Pulmonary Resuscitation, Infant Foregin-body Air-Obstruction. To make the learning more interesting, as much animation and videos were integrated. In conclusion, this e-Learning multimedia contents will be useful for student as well as members of the public. It significantly increases the chances of saving the life of person who has collapsed.

• Journal of Advanced Information Technology and Convergence
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• v.10 no.2
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• pp.167-175
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• 2020

In this paper, we propose a traffic accident detection on vehicle-mounted camera. In the proposed method, the minimum bounding box coordinates the central coordinates on the bird's eye view and motion vectors of each vehicle object, and ego-motions of the vehicle equipped with dash-cam are extracted from the dash-cam video. By using extracted 4 kinds features as the input of Bi-LSTM (bidirectional LSTM), the accident probability (score) is predicted. To investigate the effect of each input feature on the probability of an accident, we analyze the performance of the detection the case of using a single feature input and the case of using a combination of features as input, respectively. And in these two cases, different detection models are defined and used. Bi-LSTM is used as a cascade, especially when a combination of the features is used as input. The proposed method shows 76.1% precision and 75.6% recall, which is superior to our previous work.

• Journal of the Korea Computer Graphics Society
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• v.20 no.2
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• pp.1-11
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• 2014

The quality of 2D-to-3D conversion depends on the accuracy of the assigned depth to scene objects. Manual depth painting for given objects is labor intensive as each frame is painted. Specifically, a human is one of the most challenging objects for a high-quality conversion, as a human body is an articulated figure and has many degrees of freedom (DOF). In addition, various styles of clothes, accessories, and hair create a very complex silhouette around the 2D human object. We propose an efficient method to estimate visually pleasing depths of a human at every frame in a monocular video. First, a 3D template model is matched to a person in a monocular video with a small number of specified user correspondences. Our pose estimation with sequential joint angular constraints reproduces a various range of human motions (i.e., spine bending) by allowing the utilization of a fully skinned 3D model with a large number of joints and DOFs. The initial depth of the 2D object in the video is assigned from the matched results, and then propagated toward areas where the depth is missing to produce a complete depth map. For the effective handling of the complex silhouettes and appearances, we introduce a partial depth propagation method based on color segmentation to ensure the detail of the results. We compared the result and depth maps painted by experienced artists. The comparison shows that our method produces viable depth maps of humans in monocular videos efficiently.